ESPE Abstracts (2016) 86 P-P2-534

ESPE2016 Poster Presentations Fat Metabolism and Obesity P2 (56 abstracts)

Value of BMI-SDS, Waist Circumference-SDS and Waist-to-Height Ratio in the Identification of Obese Children and Adolescents at an Increased Risk for Cardio-Metabolic Complications

Jernej Kovac a , Petra Pavlic b , Brigita Perdih b & Primoz Kotnik b,


aUnit of Special Laboratory Diagnostics, University Medical Centre Ljubljana, Ljubljana, Slovenia; bMedical Faculty Ljubljana, Ljubljana, Slovenia; cDepartment of Endocrinology, Diabetes and Metabolism, University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia


Background: Determination of obese children/adolescents at an increased risk of cardio-metabolic complications is of paramount significance for early intervention.

Objective and hypotheses: To determine the value of simple anthropometric measures of obesity (BMI-SDS, waist circumference (WC)-SDS, waist-to-height ratio (WHR)) in the determination of individuals at an increased risk for selected cardio-metabolic complications (impaired glucose metabolism, dyslipidemia, increased blood pressure).

Method: 395 obese children and adolescents (212 females; age mean(SD) 12.4(3), BMI-SDS 2.8(.6), WC-SDS 3.2(.6), WHR .61(.06)) were studied. Body weight, height, WC and blood pressure were measured by a trained medical professional in the morning in a fasting state and were standardized according to the UK-WHO references. A standard 2-h OGTT was performed in all. HOMA-IR and Matsuda index were calculated. Spearman’s correlation was used to determine associations between parameters. Regression analysis with stepwise selection of parameters was used to calculate prediction models for selected cardio-metabolic complications.

Results: Several significant correlations between BMI-SDS, WC-SDS, WHR and selected cardio-metabolic complications were determined (Table 1). Correlations were not determined for total cholesterol, LDL and A1c. However, using regression analysis we determined that analyzed anthropometric measures of obesity alone describe only a small proportion in the variability of HOMA-IR (20%), HDL (6.2%), Tg (8%), SP (10%), DP (8%). WHR had the highest impact in regression analysis models except for HDL (BMI-SDS).

Table 1. (for abstract P2-P534)
HOMA-IRMatsudaHDLTgSP-SDSDP-SDS
BMI-SDS0.18*−0.10−0.23*0.27*0.28*0.15*
WC-SDS0.07−0.02−0.19*0.23*0.21*0.16*
WH ratio0.28*−0.25*−0.20*0.35*0.17*0.20*
SP, systolic pressure; DP, diastolic pressure. *P<0.001.

Conclusion: Several significant correlations between simple anthropometric measures of obesity and selected cardio-metabolic complications were determined. These measures however seem to have only a limited value in the prediction models for selected cardio-metabolic complications, WHR having the highest impact.

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